3The Magnetic Resonance Center in Florence 700bBio-labs800950850ss900700Conference roomLibrary400Workshop500Computer room600600b700ssDepartmentof Chemistry(offices, bio-labs,relaxometer, instruments..)GENEXPRESS, CRYST, CISMDaVEB Biobank
5The Magnetic Resonance Center in Florence Protein structure determinationMethodological advancements in NMRSolid state NMRICT and computational biologyElectron/nuclear relaxation (Relaxometry)Drug discoveryStructural proteomicsMetabolomics700bBio-labs800950850ss900700Conference roomLibrary400Workshop500Computer room600600b700ssWe provide access to European researchers since 1994New access program Bio-NMR ( ) started September 2010Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, GoteborgDepartmentof Chemistry(offices, bio-labs,relaxometer, instruments..)GENEXPRESS, CRYST, CISMDaVEB Biobank
6uno sguardo molecolare sulla salute e sulle malattie Metabolomica:uno sguardo molecolare sulla salute e sulle malattieClaudio LuchinatCERMUniversità di Firenze
7The Research Centers of FiorGen CERMScientific CampusSesto FiorentinoBiomedical CampusCareggi
8Scientific Publications 146 publications on high level journals, starting from 2004Independent reviewers attested the high scientific level of the Foundation“The scientific production of FiorGen is quite impressive”Prof. Arturo FalaschiScuola Normale Superiore – PisaDistinguished Scientist ICGEB TriesteAprile 2008“The scientific productivity of FiorGen is of excellent level”Prof. Giuseppe NovelliTor Vergata University of RomeUniversity of Arkansas (USA)WPQ PGx EMEA (UK)Maggio 2008
9What is Metabolomics?Metabolomics is a further “omic” science that is now emerging with the purpose of “elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites in an organism or cell”.Genomics tells you what could happen. Metabolomics tells you what has happened. Only a few thousand metabolites.!! However, not negligible external variability !! (source of noise)99
10Examples of metabolites HPyruvicadSnxloetAcetyl CoA
11+ Metabolomics Study of small molecules in biological fluids Metabolic fingerprint
152 Routes to Metabolomics (fingerprinting and pattern recognition) Two approaches:Identify as many metabolites as possibleUse the whole spectrum as a fingerprint (statistics)1234567ppmQuantitativemethodsChemometric methods(fingerprinting and pattern recognition)-25-20-15-10-5510152025-30PC1PC21234567ppmhippurateureaallantoincreatinine2-oxoglutaratecitrateTMAOsuccinatefumaratewatertaurine
16The fingerprint Metabolomics: Traditional clinical analysis: Few already known metabolites for some disease (e.g. glucose for diabetes, etc…)All metabolites are analyzed together without prior knowledge16
21METabolomic REFerence Convex hulls of 22 donors in the three most significant PCA-CA dimensionsPCA for data reductionCA for obtain well separated clustersKNN for classification99% accuracy in montecarlo cross validation“natural” gender discriminationMALEFEMALEAssfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008, 105,
22The signature of Our Body There exists an individual human metabolic phenotype (metabotype)The metabotype consists of a variable part (environment) and an invariant part (genetics + environment)The invariant part persists for at least two-three years (if the diet is averaged using collection of multiple samples)The discovery of the existence of individual metabotypes is the baseline for Biomedical ResearchesAssfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009
23Metabolomics @CERM/CIRMMP Collaborative ProjectsSPIDIA (7th framework program)Standardization and improvement of pre-analytical procedures for in-vitro diagnostics.CHANCE (7th framework program)Evaluation of the impact of nutritional criticalities in population at risk of poverty using NMR metabolomics.livSYSiPS (ErasysBio+)The sistem biology of network stress based on data generated from in vitro differentiated hepatocytes derived from individual-specific human iPS cells.ITFoM (FET Flagship Initiative)The aim of ITFoM is to develop models of human pathways, tissues, and ultimately of the whole human, to create a “virtual patient” which will enable physicians to identify personalised prevention schedules and treatments adapted to each person.Progetto COSMOS (EU Coordination action)To develop new standard for metabolomics sutdiesProgetto BioMedBridges (EU Coordination action)To develop a unified framework for biomedical studies in EuropeProgetto Melanoma (Ente Cassa di Risparmio di Firenze)New strategies for diagnosis prognosis and treatment of melanoma.
24Metabolomics @CERM/CIRMMP CollaborationsCeliac Disease (Prof. Antonio Calabrò, Careggi Hospital)Geriatric patients (Dr. Laura Biganzoli, Prato Hospital)Diabetes in young (Dr. Sonia Toni, Mayer Children’s Hospital)BPCO (Dr. Massimo Miniati, Careggi Hospital and CNR Pisa)Metastatic Colorectal Cancer (Dr. Benny W. Jensen, Herlev Hospital, Copenhagen)Periodonitis (Dr. Mario Aimetti, University of Turin)Bladder and Prostate Cancer (Dr. Marco Carini, Careggi Hospital)Cardiovascular Risk (Dr. Adriana Tognaccini, Pistoia Hospital and AVIS Toscana)Intestinal Bowel Diseases (Prof. Maurizio Vecchi, University of Milan)Heart Failure (Prof. Franco Gensini, University of Florence)Breast Cancer (Dr. Angelo Di Leo, Prato Hospital)Bariatric Surgery (Prof. Bernd Schultes, St. Gallen Hospital, Switzerland)Metabolomics of the Mitochondrion (Prof. Roland Lill, University of Marburg, Germany)Osteoarthritis (Prof. Brandi, University of Florence)Krabbe disease (Dott.sa Alice Luddi, University of Siena)Gestational diabetes (Dr. Dani, Careggi Hospital)
25Celiac Disease Metabolomics Clusterization of Celiac and Healthy subject serum spectraBertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
26Celiac Disease Metabolomics Clusterization of Celiac and Healthy subject serum spectraand corresponding Follow-upBertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
27There exist a metabolic fingerprint of celiac disease Celiac – Healthy Subjects – Cross: predicted Potential CeliacThese alteration are present also in potential celiac subjects: so they precede the intestinal damagePotential CD largely shares the metabonomic signature of overt CD. Most metabolites found to be significantly different between control and CD subjects were also altered in potential CD. Our results suggest early institution of GFD in patients with potential CDBertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J. Proteome Res. 2010
29Breast cancer metabolomics Classification between Pre-Op and Metastatic subjects.Accuracy ~80%Other comparisonsNOESYCPMGHealthy vsMetAccuracyHealthy vsMetAccuracy72.67%73.44%Healthy vsPost-opAccuracy70.00%Healthy vsPost-opAccuracy75.80%Post vsMetAccuracy74.96%Post-op vsMetAccuracy70.00%29
30Colorectal Cancer Metabolomics Serum samples from 139 HS and 155 patients with mCRC, included in a prospective phase II study of 3rd line treatment with cetuximab and irinotecanWe can discriminate healthy controls from mCRC with almost 100% accuracy.We can predict the overall survival of the patientsCross-validated results on the Training Set:Sensitivity : 79.9%Specificity: 76.4%Accuracy: 78.5%Univariate Cox Regression Analysis for the Validation Set:HR: 3.3095% CI: to 5.37P: ∙ 10-6PLS-CA model: long survival, in blue; short survival, in yellowBertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P., Cancer Res Jan 1;72(1): Epub 2011 Nov 1130303030
31Heart failure metabolomics Classification between different subgroups of Heart failure patients (1D CPMG spectra).SensitivitySpecificityAccuracyCMD vs CMS45.52%68.29%61.19%NYHA1 vs NYHA 261.88%71.42%67.71%NYHA2 vs NYHA 3/473.62%56.44%68.04%NYHA 1 vs NYHA 3/474.83%68.55%72.15%Patients vs Healthy85.11%91.04%87.29%Patients are separated from healthy, but there is not any significant difference between the disease grading that could reflect the clinical severity of the disease.Although good discrimination between healthy and HF subjects with a severe disease, if not expected, was easy to be hypothesized, a comparable good discrimination ability between healthy and HF subjects with a mild disease was unexpected and appears rather counter-intuitive.31313131
32Metabolomics of Melanoma NOESY SpectraSERUMURINESensitivity (%)Specificity (%)Accuracy (%)Healthy vs. Melanoma91.3881.6789.8995.4670.5291.37Stage I/II vs. Healthy85.4985.3485.2591.0379.0287.46Stage III/IV vs. Healthy88.8491.4089.385.4480.2582.93Stage I/II vs III/IV85.1873.2879.9475.4067.8672.983232
33Fingerprint of Obesity NW vs SO94.0OW vs SO79.6NW vs OW69.7NW vs OW+SO87.8NW+OW vs SO84.1The prediction of OW (stars) using the NW (green) vs SO (blue)model classify almost all OW as SO (except two)3333
35http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org MetabolomicaL’approccio combinato di metabolomica (Prof. Claudio Luchinat) e biobanca (Prof. Paola Turano) ci rende unici in questo settore della scienzaFROM METABOLOMICSMetabolomic analysisValidation ofsample qualityin biobanksDefinition ofnew SOPsTO BIOBANKSDalla MetabolomicaAnalisi MetabolomicaControlloQualità di campioniNelle biobancheDefinizione diNuove SOPAlle BiobancheSpettro NMR di urina di un donatore sanohttps://www. davincieuropeanbiobank.org
36http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org Fiorgen ha implementato una Biobanca su standard europei che è inserita nei programmi nazionali ed europei. Essa raccoglie campioni biologici (sangue, urine, biopsie) di molte malattie .Collezioni di campioni della Biobanca:Scompenso cardiaco (Prof. Gianfranco Gensini)Melanoma (Prof. Nicola Pimpinelli)Cancro alla mammella (Prof. Angelo Di Leo, e USA)Cancro al colon (Prof. Benny V. Jensen, Danimarca)Disturbi alla prostata (Prof. Marco Carini)Celiachia (Prof. Antonio Calabrò)Osteoporosi (Prof.ssa Maria Luisa Brandi)https://www. davincieuropeanbiobank.org
37The Future of MedicineMetabolomics can monitor the same individual in a multidimensional spacehepatocarcinomaColorectal cancercirrhosissteatosisIntestinal bowel diseaseMetabolic syndromeHealthy agingDiabetesHypertensionHearth Failure37
38Et interviene di questa come dicono e’ fisici dello etico, che nel principio del suo male è facile a curare e difficile a conoscere, ma, nel progresso del tempo, non l’avendo in principio conosciuta né medicata, diventa facile a conoscere e difficile a curare.Machiavelli, Il Principe, cap. 3
39http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org Il sognoDotare ogni cittadino di un chip in cui sono riportati il genoma, il proteoma e il metaboloma al fine di monitorarne nel tempo lo stato di salutehttps://www. davincieuropeanbiobank.org
40From general to personalized medicine The Future of MedicineFrom general to personalized medicine40
44Metabolomics @CERM/CIRMMP Metabolomics Publications Human phenotypesAssfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M. Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci U S A 2008;105(5): (IF=9.771).Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L. Individual human phenotypes in metabolic space and time. J Proteome Res Sep;8(9): (IF=5.460).Cardiovascular diseasesBernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples. J Proteome Res [Epub ahead of print] (IF=5.460).Celiac diseaseBernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011 Feb 4;10(2): (IF=5.460).Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L. The metabonomic signature of celiac disease. J Proteome Res Jan;8(1): (IF=5.460).Ozono terapyTravagli V, Zanardi I, Bernini P, Nepi S, Tenori L, Bocci V. Effects of ozone blood treatment on the metabolite profile of human blood. Int J Toxicol 2010;29(2): (IF=1.762).
45Metabolomics @CERM/CIRMMP Breast cancerTenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC, Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: A pilot study. Mol Oncol Jun 1. (IF=4.250).Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E, Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Ann Oncol 2011 Jun;22(6): (IF=6.452).Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011 Jul;43(7): Review. (IF=4.956).Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: available results, current research projects in breast cancer, and future applications. J Clin Oncol Jul 1;25(19): (IF=18.970).Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol. 2007;18 Suppl 12:xii8-14. Review. (IF=6.452).Colorectal CancerBertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res Jan 1;72(1): (IF=8.234).
46Metabolomics @CERM/CIRMMP Peridontal diseasesMario Aimetti, Stefano Cacciatore, Antonio Graziano and Leonardo Tenori. Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics; Online First™ (IF=3.608).Standard Operating ProceduresBernini P, Bertini I, Luchinat C, Nincheri P, Staderini S, Turano P. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR Apr;49(3-4): (IF=3.047).The future of medicineBertini I; Luchinat C; Tenori L. Metabolomics for the future of personalized medicine through information and communication technologies. PERSONALIZED MEDICINE Volume: 9 Issue: 2 (IF=0.783).
47Our interest in metabolomics Metabolic signature of individuals:Metabolic phenotypeMetabolic signature of diseasesCoeliac diseasetumor metastasisheart failure, pulmonary diseases,etc…Metabolites and biobank samplesSensitive reporters of stabilityAssess sample preparation and preanalytical proceduresSOP
48Metabolomics steps Handling and preparation of samples NMR analysis Metabolites identificationStatistical analysisData processing and bucketing484848
49BioBank Project Collect Store Processing Distribute Biological samples for scientific research
50The need for individual metabolomic screening The Future of MedicineThe need for individual metabolomic screeningWe are proposing to collect individual metabolomics data for a large screening of the Tuscany population50
52How was FiorGen bornFiorGen Foundation, a “non-profit organization of social utility” (ONLUS), was founded in 2002, with the purpose of favoring scientific, cultural and social development.FiorGen Foundation is the result of a strong link between different scientific actors such as the Magnetic Resonance Center (CERM) of the Scientific Campus of Sesto Fiorentino and the Biomedical Campus of Careggi, which has been supported by the Chamber of Commerce, Industry and Handicrafts of Florence and the Ente Cassa di Risparmio of Florence.
61Research Areas of FiorGen Research Area 1: Bersagli e farmaci antitumoraliAgonisti di recettori nucleari nella modulazione della crescita ed invasività tumoraleDelezione organo specifica del recettore ARP-1 in modelli muriniResearch Area 2: Fisiopatologia e farmacogenetica delle malattie cardiovascolariProgetto Malattia Aneurismatica e CarotideaProgetto variabilità nella risposta alla terapia antiaggregante (aspirina e clopidogrel)Research Area 3: Origine malattie geneticheStudio delle basi genetiche della predisposizione a neoplasie umaneStudi sull'origine della Sclerosi Laterale AmiotroficaCaratterizzazione strutturale della proteina beta amiloide coinvolta nel morbo di AlzheimerResearch Area 4: MetabolomicaResearch Area 5: BioBanca da Vinci European BioBank - daVEBResearch Area 6: Melanoma: nuovi possibili biomarcatori di diagnosi e progressione